Model Card for mmatinm/mpersian_xlm_roberta_large
This model is a fine-tuned XLM-RoBERTa Large for Persian question answering, trained on the PersianQA dataset.
It was originally based on pedramyazdipoor/persian_xlm_roberta_large, which was fine-tuned on the PQuAD dataset.
Model Details
Model Description
- Developed by: mmatinm
- Base model: XLM-RoBERTa Large (from Hugging Face Transformers)
- Language(s): Persian (fa)
- Task: Extractive Question Answering (SQuAD v2 style)
- Finetuned from:
pedramyazdipoor/persian_xlm_roberta_large
Model Sources
- Repository: GitHub Repo
- Demo: Colab Demo
Uses
Direct Use
- Answering questions given a Persian context paragraph.
- Can be used as a QA backend in chatbots or search engines for Persian content.
Downstream Use
- Further fine-tuning for domain-specific QA in Persian.
- Integration into multi-lingual QA systems.
Out-of-Scope Use
- Generative QA (this is extractive only).
- Languages other than Persian.
Bias, Risks, and Limitations
- Model performance is dependent on the quality and coverage of PersianQA.
- May fail on highly domain-specific or slang-heavy texts.
- May return incorrect spans for ambiguous questions.
How to Get Started with the Model
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
repo_id = "mmatinm/mpersian_xlm_roberta_large"
tokenizer = AutoTokenizer.from_pretrained(repo_id)
model = AutoModelForQuestionAnswering.from_pretrained(repo_id)
Results
| Model & Method | F1 Score | EM Score | No-Answer F1 |
|---|---|---|---|
| XLM-R ( LoRA + QA Head) | 85.3 | 71.6 | 90.7 |
Citation
@misc{mmatinm2025xlmr,
title={Persian XLM-RoBERTa Fine-Tuned on PersianQA},
author={Matin M.},
year={2025},
publisher={Hugging Face}
}
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